Potential Function

Potential functions are mathematical tools used to model various systems by assigning a scalar value to each state, guiding processes towards optimal solutions or desired configurations. Current research focuses on applications ranging from robotics path planning (using modified potential fields to avoid local minima) and sensor network localization (employing potential games and duality theory for efficient distributed solutions) to machine learning (developing novel potential functions via PDEs for improved online learning algorithms and using them for object recognition in navigation). These advancements contribute to improved efficiency and robustness in diverse fields, offering solutions to complex optimization problems and enabling more sophisticated autonomous systems.